WIND EROSION

From Wind Erosion Research unit UAUA. AKA Kansas xate unzversrty

IN THE UNITED STATES

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es and then to summarize both the current extent of develop wind erosion prediction lechnology.

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owing of the prairie soils in the semi-arid plains regions follow t in the 1930's resulted in "black blizzards". These storms made and also deposited large amounts of topsoil on eastern regic ding the capitol, Washington, D.C. (Hurt 1981). . . .. ~ * . . . . .~~ - c ~~. ~ . ~ . -1 ~~

The purposes or tnls revon are io cive a mer nmoricai DersDecrive on wind erosion in the United Stab the problem and research efforts to

The presence of large areas 01- loess soils in the United States confirms that wind erosion and deposition were important geologic processes in past times. Nevertheless, the activities of man often accelerate wind erosion, and dust stroms have been reported by farmers since the earliest settlements in the United States (Lyles 1985). However, widespread pl led by the severe drough life on the plains harsh ins of the country, i nch

A qualitative unoersrariamg or me prmcpes or wmu erosion cmuui was known before the 1930's. These principles include: a) establish and maintain vegetation or vegetative residues, b) produce or bring to the surface nonerodible aggregates or clods, c) reduce field length along the prevailing wind direction, d) roughen the field surface, and e) protect fields with wind barriers. Neverlheless, the dust storms of the 1930's brought widespread public recognition that both additional research and implementation of control measures were needed.

Two events in the 1940's marked thi iantitative research on wind erosion in the United SI a book by British physicist, R.A. Bagnold (1941) coLuvIIuIIIIIcLLL ul a yyyn wlLid erosion research project

5 beginning of the modem era of qi tates. These were the publication of .."A ,."+"l.,;"l.-""* ,.c " T T P n . 4 ..,:*

at Manhattan, Kansas.

Extent of problem

Cropland

On cropland, about 70 million ha are eroding at rates that exceed lwice the tolerance level for sustainable production (USDA 1989). Sheet and rill erosion by water cause 60 percent of the soil loss, and wind erosion causes 40 percent. Cropland regions where

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Winderosion ._.. 21

28 L. J. Haten

ice of wind erosion. When precipitation is low in lease markedly in the second year (Hagen and Woo Soil Conservation Service has offered assistance ti trol systems for many years. However, in 1985 .~ . . . . . , . . .

wind erosion is a problem have been summarized by the USDA Soil Conservation Service (Fig. 1). The largest cropland region affected by wind erosion is in the Great Plains region extending from Texas to Canada. High wind speeds in spring and a semi-arid climate combine to make this region paticularly vulnerable. However, many croplands near the Great Lakes, humid coastal areas, and irrigated areas in the west also are subject to wind erosion. Sandy and organic soils without vegetation often are affected most by wind erosion in these areas. In the Great Plains, the USDA Soil Conservation Service reports wind erosion conditions each month for the period November through May. The total land damaged annually (i.e., soil loss exceeding about 34 mT/ha each year) ranges from a low of about half million ha to more than 6 million ha (Fig. 2). Variability of precipitation is the major cause of the wide swings in the annual occurre] two successive years, dust storms inn druff 1973).

The USDA 3 producers in design of erosion con as part of the Food Security Act, development ana suosequenr impiemenrarion or conservation plans were required on highly erodible croplands in order for producers to receive federal crop subsidies. An additional part of the Act, called the Consemation Reserve Program (CRP), also was initiated to reduce erosion (Kozloff and Wang 1992). The CRP offers farmers annual rental payments in exchange for removing highly erodible land etirely from crop production and placing it under permanent vegetative cover for 10 years. The progam is 15 million cropland II conipliancf

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approaching the current goal of establishing permanent vegetative cover on ha of formerly highly erodible croplands. When the CRP contracts expire, the lay be returned to production, but will generally he subject to conservation 5 tules.

in the United States (USDA 1989). Ove s caused deterioration on many rangelar . . 1 . . .. 1 1 . .

rangelands :rgrazing, particularly during the last century, ha ids. The health of rangeland and the degree to wnicn 11 will remona LO unurovea management are often judged by comparing the present vel y this standard, abont 60 percent of rang n rangeland is difficult to quantify. However, it is estimated that about ZX million ha OK nonfederal rangelands are eroding at rates that prevent sustainable production.

- pation of a site to the climax vegetation. B eland currently needs improvement. Erosion o

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Wina brosion rreaicrion

Wind Erosion Equation (WEQ) i I

Based on research done in the 1950’s and early 1960’s, a computational procedure, named the Wind Erosion Equation, was developed (Woodruff aud Siddoway 1965).

Winderosion ....

i WEQ is currently the most widelv used method of estimatmg wmd erosion m tlie united States. The WEQ is expi 1 ~

.essed in functional form as:

E = f(I,K,C.L,V)

where: E - potential annual soil loss in tons per ha, I - soil erodibility index in tons per ha, K - soil ridge rouglm C -climatic factor, L - field length facto V - vegetative factor

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Wind Erosion Pre ..

le climate factor, c<m be calculated

diction System (WE1

erosioii is now a serious problem in many lands, a .. . . ~.

I human impact on . ~ ~ ~~~

The WEQ is largely ll..~ .._- -l_ yy..L-.., ..- _.__ r-- lyl l.. ..._ Plains. Recent advances in erosion theory and the availability of new field measurements of wind erosion (Fryrear and Saleh 1993) provide a basis to improve WEQ predictions, particularly in regions outside the Great Plains. Hence, a revised Wind Erosion Equation (RWEQ) is being develped currently by USDA scientists and should be released for public use during 1994. The RWEQ will operate on time-steps of about two weeks and he coupled to data bases from which some of the input parameters, such as tl

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Wind nc the global environment is an issue of international concern. To adequately deal with issues such as probability of erosion events, generation of dust for long-range transport, and the consequences of complex land management strategies, new prediction technology is needed. Widespread availability of personal computers also makes it feasible to deliver technology in the form of computer models to many users (Shaw 1991). Hence, the USDA appointed a multi-disciplinary team of scientists and engineers to take a leading role in developing WEPS. This model should he available for widespread distribution in 1996.

s a field or, at most, a few adjacent fields (Hagen lrri D). w c r h ourpur IS average soil loss/deposition over user-selected time intervals and accounting regions within the simulation region. WEPS also has an option to provide users with individual soil loss components for soil-size fractions in creep, saltation, and suspension. The structure of WEPS is modular and consists of a MAIN (supervisory) program, a user-interrace section, seven suhmodels, and an output section (Fig. 3).

The WEATHER submodel generates meteorological variables to drive the other submodels using monthly statistical data in the climate data base (Skidmore and Tatarko 1990, Nicks 1985

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WEPS is a daily simulation moc I , ~

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le1 in which the simulation region i **., > .../-.." ~ . . . .. 1

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WINn FRflSlflN

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Ryc. 3. ModuIoowy System Prognomwuniu Erozji Eolicznej (WEl'S) zbudowany L pliMw, bac danych i submodeli

Wmdcrosion .. 3 1 I I

Biomass accounting in WEF’S is accomplished by the CROP GROWTH and DECOMPOSITION submodels using specific crop parameter values from a data base. Crop growth is simulated by a generalized submodel that calculates potential growth of leaves, stems, roots, and yield components. The submodel uses revised routines derived from the EPIC model described by Williams, Jones, and Dyke (1988). The potential growth is modified by temperature, fertility, and moisture stresses. The DECOMPOSITION submodel predicts the biomass residues in the standing, flat, and buried categories; hatvest removes biomass from some of the categories. The SOIL submodel predicts the temporal soil properties between erosion and tillage events. The temporal properties include scales of random and oriented roughness; size distribution ‘and dry stability of aggregates; thickness, dry stability, and cover fraction of cmst/consolidated zone; and mass of l ose , erodible particles on the crust (Zubcck 1991).

The HYDROLOGY submodel simulates the soil water with particular emphasis on surface soil wetness (Durar et al. 1993). In addition, energy balaxces including soil freezdthaw cycles, snow melt and redistribution, and irrigation will be simulated in this submodel.

The MANAGEMENT submodel modifies the soil and biomass properties by tillage, . . iarvest, burning, etc. (Wagner and Ding 1993). The management data basc consists of xuameters for specific tillage and harvesting equipment.

EROSION

WIND

SALTATION

CREEP

- TRAPPINO CLODICRUST , -

- ABRASION

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SURFACE REARRANGEMENT (LOSS/DEPOSITION) I

Fig. 4. Processes simulated in WEPS EROSION submodel wth n bare soil Ryc. 4. Praees symulowmy w submodelu EROZIA, WEPS-u, dhnieosionietej &by

The EROSION submodel simulates soil loss and deposition during periods when wind speed exceeds lhe erosion threshold. Soil transport by wind is modeled as conservation of mass of two species (saltation- and creep-size aggregates) with two sources of erodible material (emission of loose soil and abrasion of clod/crust) and two sinks (surface trapping and suspension) (Hagen 1991a) (Fig. 4).

References

I): The Physics of Blow Sand and Desert Dunes. Chapman a. Hall, London. ET J.L., Evett S B , Skidwre EL. (1993): Measured and simulated surface soil drying. reSS). . . . . ̂̂ .. -. . . . . . . . . . . . . - .. - ...........

991s): Wind erosion mechanics: abrasion of aggregated sail. Trans. Am. SOC. Agr. Engm., 34.4

1991b): A wind emsion prediction system lo meet user needs. J. Soil Water Cons., 46, 2

Bq~rnld RA. (194 Dirrar A.A., Stciu

A w n . J. (in p1 f i y l w r D.W., Salen A. ww: rma wmo croston: w t m ommuuon. mtsc I . , 155.4: 294-iuu. HagenLJ. (1

831-537. Hagen L-I. (

105.1 11. Hagen L.J., WoodmIYNP. (1973): Air pollution from dust storms in &e Great Plains. Ahnos. Environ., 7:

323-332. HmtD.R(l981): TheDustBowl.Nelson-Hall,Chicilgo. Kozloff K., Wnng Y. (1992): Improving cost effectiveness of retiring erodible land from mop production. J.

Lylcs 1,. (1985): Predicting and eonlrolling wind erosi, Nicks A.D. (1985): Generetion of climate data. Roc. I

ShawR.R. (1991): Managing the land a technologyp

SuilWatcrCons., 47.2 191-194.

- Am. SOC. A w n . ARS-30 297-300.

....................... ....... .. Skidlwre E.L., Tntarko J. (1990): Stochastic wind .- =. a.. Engin.,33,6: 1893-1899.

nonfodeml lend in the United Statcs. Washington, D.C.: US. Government Printing Oftice.

Agr. Engin. (in press).

index calculator. Ed. J.R. Williims. Temple, Tx: USDA-ARS.

US. Deparlment of Agriculhlre. 1989. The second RCA appraisal: soil, water and related resou~es on

Wagner L.E., D h g D. (1993): Stochastic modeling of tillage induced aggregate breakage. Trans. Am. SOC.

William J.R., Joncs C.A., Dyke P.T. (1988): The EPIC madeel, Volume 1. EPIC, the erosion productivity

on. Agric.HisL.59.2 205-214. ,f Natural Resources Modeling Symp. US. Depl. Agric.

erspeclive. J. Soil Water Cans., 46, 6: 406-408. simulation h r emdon rnorlclinv Trnm A m So? A m

Waodr"fCN.P., Siddoway F.11. (1965): Awind erosion equation. SoilSci. SOC. Am. Proc., 29.5: 602-608, Zol~ckT.M.(1991):Soilproperti~iesaffectingwnderosion. J. SoilWaterCons.,46,2: 112-118.

EROZJA EOLICZNA W USA

S t r e s z c z e n i e

W Stanach Zjdnocronych okolo 70 mln ha Suntbw upramych ole&',. cLyAJ.. yuLL..p F.,.y ,)I,,,. i i erozja eoliczna powodup okolo 40% og6hych slmt &by.

W niniejszej praacy przedstawiono map$ wystppowanh emzji eulicrnej nn terytorium USA oraz jej nalatenie w paszczeg6lnych latach nn Wielkiej Rdwnilue. Paedstlwiono tlkie ewohicje fzw. R6wnaniu Emzji Wielrznoj (WEQ) do obecnie wykonystywanego przez USDA SCS Systemu Proognozowania Erwzji Eolicznej WEPS). Om6wiono budowg og6lna tego modehi maz fimkcje poszczegblnych submodeli, jlk tci efekt symulacji procesu eolicmego dla przypypadku glebynieoshni@tej.